Mohammad Shokoohi-Yekta

Generalizing Dynamic Time Warping to the Multi-Dimensional Case Requires an Adaptive Approach

Eamonn J. Keogh, Hongxia Jin, Mohammad Shokoohi-Yekta, 2014 .

Towards wind farm performance optimization through empirical models

Jianhui Chen, Satish Iyengar, Mohammad Shokoohi-Yekta, 2014, 2014 IEEE Aerospace Conference.

On the Non-Trivial Generalization of Dynamic Time Warping to the Multi-Dimensional Case

Jun Wang, Eamonn J. Keogh, Mohammad Shokoohi-Yekta, 2015, SDM.

Generalizing DTW to the multi-dimensional case requires an adaptive approach

Jun Wang, Hongxia Jin, Eamonn J. Keogh, 2016, Data Mining and Knowledge Discovery.

Clustering in the Face of Fast Changing Streams

Eamonn J. Keogh, Eamonn Keogh, Nurjahan Begum, 2016, SDM.

A clustering-based rule-mining approach for monitoring long-term energy use and understanding system behavior

Mohammad Shokoohi-Yekta, Unmesh Kurup, Seyed Hamid Mirebrahim, 2017, BuildSys@SenSys.

Discovery of Meaningful Rules in Time Series

Eamonn J. Keogh, Mohammad Shokoohi-Yekta, Yanping Chen, 2015, KDD.

Parameter-Free Audio Motif Discovery in Large Data Archives

Eamonn J. Keogh, Mohammad Shokoohi-Yekta, George Papageorgiou, 2013, 2013 IEEE 13th International Conference on Data Mining.